Embodiments of the present invention relate generally to process control techniques. More particularly, embodiments of the present invention relate to dynamic model predictive control and optimization of bulk material blending processes.
Bulk material blending generally refers to a process in which multiple material streams are mixed to create a particular blended product for storage, stockpiling, or downstream processing. By way of example, bulk material blending techniques may be applicable to the manufacture of a number of blended materials across different industries, such as cement blending (e.g., both raw mix and clinker mix), coal blending, as well as other various mineral and/or liquid blending processes.
A frequent challenge that may arise in any bulk material blending process is controlling and maintaining the stability of the raw material chemistry in creating the blended product. To provide one example using a competitive market, such as the cement market, one challenge may be to produce cement conforming to certain quality specifications while using the lowest cost materials. Accordingly, plant and quarry management decisions, weather conditions, as well as material delivery logistics, can impose long term chemistry variations in the overall material blending process. For instance, it may not always be feasible to extract the best limestone (e.g., having a high purity or concentration of calcium carbonate (CaCO3)) due to limitations regarding either cost or logistics. Rather, in some instances, to obtain a desired amount of a particular desired material, it may be necessary or even more cost effective to transport and/or extract the desired material from bulk materials having a lower concentration of the desired material.
Further, throughout the material blending process, it may be necessary to maintain the average of the raw material chemistry in as stable a manner as possible while maintaining the production of a blended product that satisfies one or more desired quality specifications. For example, referring back to the cement manufacturing example discussed above, certain applicable quality standards implemented with regard to the raw mix of cement materials may be intended to minimize the total heat consumption, and thus overall energy requirements, for clinkering, as well as ensure that the resulting blended material is within product specifications. Additionally, unstable chemistry that fails to conform to these quality standards may lead to unstable kiln operation for clinkering, as well as produce a product that fails to meet certain quality guidelines, and thus may meet industry standards with respect to product specifications.
Historically, engineers at blending plants and quarries have attempted to manually control the proportioning set points for raw feed materials and/or the feed rates of the raw materials to meet certain quality parameters. In some instances, these quality parameters may be based on maintaining certain desired relationships and ratios between one or more materials in the blending process. Such material relationships may be referred to as “moduli.” However, there may be a mathematically infinite number of solutions to satisfy requirements for the one or more desired moduli. Thus, engineers and operators often resort to on-site trial and error in adjusting the proportioning set points of raw material feeds to produce a product that is in conformance with one or more desired moduli. Further, even if manual control of the blending process based on a determined moduli relationship may be achieved, such control does not take cost optimization considerations into account. Accordingly, to effectively control the material chemistry in a material blending process while taking raw material cost into account, an improved technique for controlling material blending processes to reduce the overall deviations from a particular quality target is needed.